Suchergebnisse

"This book analyses the question of the right to the city, informal economies and the non-western shape of neoliberal governance in India through a new analytic: the right to sell. The book examines why and how states attempt to curb, control, and eliminate markets of urban informal street vendors. Focusing on Kolkata, the author provides a theoretical explanation of this puzzle by distilling and analysing the inherent tensions among the constitutive elements of neoliberal governance, namely, growth imperative, market activism, and corporatization, and demonstrates its implications for the formal/informal boundaries of the economy. A useful addition to the existing literatures on the right to the city, informal economies, and the shapes that neoliberalism takes in the non-west, the book provides a non-western counter to accounts of neoliberalism and will be of interest to academics working in the fields of South Asian Studies, Urban Studies, and Political Economy"--

Acknowledgments; Part I Anxiety of Markets Chapter 1: Introduction; Chapter 2: Neoliberalism, (In)formality, and Markets; Part II Politics of Street Vending Chapter 3: Selling of Spaces/Spaces of Selling; Chapter 4: Politics of Disruption; Part III Conflicts/Compromise Chapter 5: Rights or Rightlessness?; Chapter 6: Conclusion

Gowri Shankar : a.k.a. Auto Shankar -- Beer Man : beerly a serial killer -- K.D. Kempamma : Cyanide Mallika -- Thug Behram : the world's most dangerous serial killer -- Stoneman : India's most elusive serial killer -- Koli and Pandher : the Nithari-Kaand killers -- Raman Ragav : a.k.a. India's Jack the Ripper -- Darbara Singh : a.k.a. Baby Killer -- Jakkal, Sutar, Jagtap and Shah : the Joshi-Abhyankar massacre -- Amardeep Sada : the world's youngest serial killer -- Cyanide Mohan : the teacher-turned-serial-killer -- Anjanabai, Seema Gavit and Renuka Shinde : child killers of India.

This book examines Warren, a suburb of Detroit, Michigan, as a shrinking city facing a crisis of economic downturn, automotive restructuring, high unemployment, and real estate foreclosures. The author explores Warren's attempt to develop planning strategies, culturally-based initiatives, community design projects, and creative partnerships in the region in order to address the challenges of shrinkage and foreclosures at multiple scales. Global urban development is currently characterized by varied combination of metropolitan growth and urban core shrinkage. While much of the shrinkage is concentrated in central cities, first suburbs are now facing the same problem. The Warren case illustrates opportunities for flexible policies combining rightsizing, shared maintenance, and incremental development in struggling first suburban communities, which are less studied and often ignored.--

"The NBER Bulletin on Aging and Health provides summaries of publications like this. You can sign up to receive the NBER Bulletin on Aging and Health by email. The United States aspires to use information from comparative effectiveness research (CER) to reduce waste and contain costs without instituting a formal rationing mechanism or compromising patient or physician autonomy with regard to treatment choices. With such ambitious goals, traditional combinations of research designs and analytical methods used in CER may lead to disappointing results. In this paper, I study how alternate regimes of comparative effectiveness information help shape the marginal benefits (demand) curve in the population and how such perceived demand curves impact decision-making at the individual patient level and welfare at the societal level. I highlight the need to individualize comparative effectiveness research in order to generate the true (normative) demand curve for treatments. I discuss methodological principles that guide research designs for such studies. Using an example of the comparative effect of substance abuse treatments on crime, I use novel econometric methods to salvage individualized information from an existing dataset"--National Bureau of Economic Research web site

"The NBER Bulletin on Aging and Health provides summaries of publications like this. You can sign up to receive the NBER Bulletin on Aging and Health by email. Public subsidization of technology assessments in general, and Comparative Effectiveness Research (CER) in particular, has received considerable attention as a tool to simultaneously improve patient health and lower the cost of health care. However, little conceptual and empirical understanding exists concerning the quantitative impact of public technology assessments such as CER. This paper analyses the impact of CER on health and medical care spending interpreting CER to shift the demand for some treatments at the expense of others. We trace out the spending and health implications of such demand shifts in private- as well as subsidized health care markets. In contrast to current wisdom, our analysis implies that CER may well increase spending and adversely affect patient health, particularly when treatment effects are heterogeneous across patients. We simulate these economic effects for antipsychotics that are among the largest drug classes of the US Medicaid program and for which CER has been conducted by means of the CATIE trial in 1999. Using conservative estimates, we find that if Medicaid would have eliminated coverage for the least cost-effective treatments of the CATIE trial then under homogeneous effects, it would save about 90% of the $1.3B Medicaid class sales annually in non-elderly adult patient with schizophrenia. However, taking into account the observed heterogeneity in treatment effects, it would incur a loss of health valued annually at about 98% of class spending and thus a net loss of about 8% of annual class spending"--National Bureau of Economic Research web site

"Under the assumption of no unmeasured confounders, a large literature exists on methods that can be used to estimating average treatment effects (ATE) from observational data and that spans regression models, propensity score adjustments using stratification, weighting or regression and even the combination of both as in doubly-robust estimators. However, comparison of these alternative methods is sparse in the context of data generated via non-linear models where treatment effects are heterogeneous, such as is in the case of healthcare cost data. In this paper, we compare the performance of alternative regression and propensity score-based estimators in estimating average treatment effects on outcomes that are generated via non-linear models. Using simulations, we find that in moderate size samples (n= 5000), balancing on estimated propensity scores balances the covariate means across treatment arms but fails to balance higher-order moments and covariances amongst covariates, raising concern about its use in non-linear outcomes generating mechanisms. We also find that besides inverse-probability weighting (IPW) with propensity scores, no one estimator is consistent under all data generating mechanisms. The IPW estimator is itself prone to inconsistency due to misspecification of the model for estimating propensity scores. Even when it is consistent, the IPW estimator is usually extremely inefficient. Thus care should be taken before naively applying any one estimator to estimate ATE in these data. We develop a recommendation for an algorithm which may help applied researchers to arrive at the optimal estimator. We illustrate the application of this algorithm and also the performance of alternative methods in a cost dataset on breast cancer treatment"--National Bureau of Economic Research web site

With special reference to Bengal, India